Medical Equipment Failure Rate Analysis Using Supervised Machine Learning.

Machine learning is widely used to identify patterns in data and to assemble models that anticipate future outcomes based on historical data. One of the critical components required for efficient healthcare services provision is medical equipment. Applying machine learning for failure rate modeling and prediction is of great importance. Therefore, two different stochastic models, ARMA and GARCH models, were utilized to analyze failure rate data. The outcome of each model was compared with previous work so that to achieve the best model that represent the failure rate data.